Context based identification of non-relevant verbal communications

ABSTRACT

A computer-implemented method includes identifying a first set of utterances from a plurality of utterances. The plurality of utterances is associated with a conversation and transmitted via a plurality of audio signals. The computer-implemented method further includes mining the first set of utterances for a first context. The computer-implemented method further includes determining that the first context associated with the first set of utterances is not relevant to a second context associated with the conversation. The computer-implemented method further includes dynamically muting, for at least a first period of time, a first audio signal in the plurality of audio signals corresponding to the first set of utterances. A corresponding computer system and computer program product are also disclosed.

BACKGROUND

The present disclosure relates generally to multi-party communicationsand in particular to filtering communications.

A multi-party communication or teleconference (i.e., telephoneconference, audio conference, and video conference) is the live exchangeand mass articulation of information among several individuals.Teleconferences enable individuals to communicate or conduct meetingswithout requiring all of the participants to be physically present inthe same location. Accordingly, teleconferences can reduce or eliminatethe time and expense required to travel to a common location in order toconduct a meeting. During a teleconference, individual participantslisten and speak with other participants via telephones linked by atelecommunications system. If multiple participants are located in thesame space, a speakerphone may be used. A speakerphone allows multipleindividuals to participate in a conversation by broadcasting the voicesof participants on the other end of the phone line, while the microphonecaptures the voices of those using the speakerphone. However, themicrophone may also capture conversations and noises that are irrelevantor distracting to the current conversational topic.

SUMMARY

A computer-implemented method includes identifying a first set ofutterances from a plurality of utterances. The plurality of utterancesis associated with a conversation and transmitted via a plurality ofaudio signals. The computer-implemented method further includes miningthe first set of utterances for a first context. Thecomputer-implemented method further includes determining that the firstcontext associated with the first set of utterances is not relevant to asecond context associated with the conversation. Thecomputer-implemented method further includes dynamically muting, for atleast a first period of time, a first audio signal in the plurality ofaudio signals corresponding to the first set of utterances. Acorresponding computer system and computer program product are alsodisclosed.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a functional block diagram of a computing environment suitablefor operation of a teleconference management program in accordance withat least one embodiment of the invention.

FIG. 2 is a flow chart diagram depicting operational steps for ateleconference management program in accordance with at least oneembodiment of the invention.

FIG. 3 is a block diagram depicting components of a computer suitablefor executing a teleconference management program in accordance with atleast one embodiment of the invention.

DETAILED DESCRIPTION

Teleconferences are prone to secondary conversations and backgroundnoises that can be distracting to the current speaker, as well as tothose who are listening. These secondary conversations and backgroundnoises tend to become amplified as the number of participants increases.Furthermore, teleconferences are often conducted by individuals whoreside in different time zones. This too can result in an increase inthe number of secondary conversations and background noises. Forexample, a teleconference is held between individuals residing in theUnited States and India. If the teleconference is scheduled to begin at10:00 am Eastern Standard Time (EST), the teleconference will begin at7:30 pm Indian Standard Time (IST) for those individuals who live inIndia. In this scenario, the individuals residing in the United Statesare likely to be in a workplace setting, while those individualsresiding in India are likely to be at home. Accordingly, secondaryconversations may occur between a person listening in on the call and afamily member present within the household. Similarly, backgroundnoises, such as radios, televisions, and appliances may be transmittedto the other participants of the teleconference.

Generally, lines with poor audio quality or unwanted sounds can beidentified. However, a current solution to eliminating lines with pooraudio quality or unwanted sounds requires an individual, such as acurrent speaker or a meeting moderator, to verbally request thatindividuals on other phone lines mute their phones or please be quiet.This can lead to a disruption from a current conversation, as well as aloss of train of thought by the current speaker.

Embodiments of the present invention provide for the identification andelimination of non-relevant verbal communications (i.e., utterances) andbackground noises. The content of verbal communications generated byspeakers during a conference call are analyzed to determine whether theverbal communications are contextually relevant to the meeting. In anembodiment of the invention, the content of a current speaker isanalyzed to determine whether the content of the current speaker iscontextually relevant to the content of a previous speaker.

Embodiments of the present invention provide for analyzingconversational keywords, phrases, topics, and themes over time todetermine whether specific conversations are outside an expected contextof a conference or meeting. Embodiments of the present invention providefor inferring additional potential topics of discussion based on ageneral meeting agenda. Embodiments of the present invention provide forreal-time analysis and modification of meeting topics to determinefuture trends and themes that may be contextually relevant.

Embodiments of the present invention provide for dynamically muting atelephone, speakerphone, or any other generally known communicationsdevice if the content of a conversation received from a device isdetermined to be outside an expected context of a current conversationaltopic. In some embodiments, a conversation between participants whoseline has been muted is monitored for content relating to the currenttopic of discussion. In these embodiments, the telephone or speakerphoneis dynamically unmuted if the conversation between these participants islater determined to be contextually relevant to the current topic ofdiscussion.

Embodiments of the present invention provide for redacting and/oreliminating unrelated conversations and background noises from aconference call. In embodiments of the invention, a centralizedconferencing system is configured to allow for the buffer or delay ofconversations so that irrelevant conversations are removed or redactedprior to being heard by other members. In some embodiments, anotification is sent to those members whose line has been muted.Examples of a notification may include, but are not limited to, astandard message service (SMS) (i.e., text-message) notification, anemail notification, a verbal notification, and a visual notification(e.g., blinking light on a communications device) that is transmitted tothe line that has been muted. In an embodiment, a text translation ofany unrelated conversations redacted, eliminated, or otherwise mutedfrom the conference call is provided concurrently with a conference ormeeting. For example, a transcript of utterances that are muted ispresented to conference members via pdf, email, or SMS notification. Inanother example, utterances that are muted are displayed as subtitles ona display screen during a video broadcast of a conference. In someembodiments, an audio copy of any unrelated conversations redactedand/or or eliminated from the conference call is provided to themembers. Various embodiments of the present invention may address orimprove upon some or all of the aforementioned problems ordisadvantages, however it will be understood that addressing anyparticular problem or disadvantage is not a necessary requirement forthe practice of all embodiments of the present invention.

Referring now to various embodiments of the invention in more detail,FIG. 1 is a functional block diagram of a computing environment,generally designated 100, suitable for operation of a teleconferencemanagement program 101 in accordance with at least one embodiment of theinvention. FIG. 1 provides only an illustration of one implementation ofthe invention and does not imply any limitations with regard to theenvironments in which different embodiments may be implemented. Manymodifications to the depicted environment may be made by those skilledin the art without departing from the scope of the invention as recitedby the claims.

Computing environment 100 includes computer system 102, user devices103, and conversation database 104 interconnected over network 105.Network 105 can be, for example, a telecommunications network, a localarea network (LAN), a wide area network (WAN), such as the Internet, ora combination of the three, and can include wired, wireless, or fiberoptic connections. Network 105 may include one or more wired and/orwireless networks that are capable of receiving and transmitting data,voice, and/or video signals, including multimedia signals that includevoice, data, and video information. In general, network 105 may be anycombination of connections and protocols that will supportcommunications between computer system 102, plurality of user devices103, conversation database 104, and other computing devices (not shown)within computing environment 100.

Computer system 102 can be a standalone computing device, a managementserver, a web server, a mobile computing device, or any other electronicdevice or computing system capable of receiving, sending, and processingdata. In other embodiments, computer system 102 can represent a servercomputing system utilizing multiple computers as a server system, suchas in a cloud computing environment. In an embodiment, computer system102 represents a computing system utilizing clustered computers andcomponents (e.g., database server computers, application servercomputers, etc.) that act as a single pool of seamless resources whenaccessed within computing environment 100. Computer system 102 includesDDI program 101. Computer system 102 may include internal and externalhardware components, as depicted and described in further detail withrespect to FIG. 3.

User devices 103 can be a laptop computer, tablet computer, smartphone,smartwatch, or any programmable electronic device capable ofcommunicating with various components and devices within computingenvironment 100, via network 105. In general, user devices 103 representany programmable electronic devices or combination of programmableelectronic devices capable of executing machine readable programinstructions and communicating with other computing devices (not shown)within computing environment 100 via a network, such as network 105.

In embodiments of the invention, user devices 103 include one or morespeakerphones for use in an audio or video conference. A speakerphone isa telephone that includes at least a loudspeaker, a microphone, and oneor more microprocessors. In embodiments of the invention, user devices103 include one or more voice over internet protocol (VoIP) compatibledevices (i.e., Voice over IP, IP telephony, broadband telephony, andbroadband phone service). VoIP is a methodology and group oftechnologies for the delivery of voice communications and multimediasessions over internet protocol (IP) networks, such as the Internet.VoIP may be integrated into smartphones, personal computers, and anygeneral computing devices, such as user devices 103, which are capableof communication with network 105.

A user device may include a user interface (not independently shown onFIG. 1). User interface 106 provides an interface between a user deviceand computer system 102. In one embodiment, the user interface may be agraphical user interface (GUI) or a web user interface (WUI) and candisplay text, documents, web browser windows, user options, applicationinterfaces, and instructions for operation, and include the information(such as graphic, text, and sound) that a program presents to a user andthe control sequences the user employs to control the program. Inanother embodiment, the user interface may also be mobile applicationsoftware that provides an interface between each user device andcomputer system 102. Mobile application software, or an “app,” is acomputer program that runs on smartphones, tablet computers,smartwatches and any other mobile devices.

Conversation database 104 is configured to store various information tobe accessed and analyzed by teleconference management program 101. Insome embodiments, conversation database 104 includes conferenceinformation (e.g., text materials, slides, meeting agendas, onlinerelated materials, calendar information, and meeting participants) usedto determine contextual information about a conference. In embodimentsof the invention, conversation database 104 includes key terms andphrases spoken during a conference. In embodiments of the invention,teleconference management program 101 extracts topics or concepts ofconversations during a conference and stores this information inconversation database 104. In some embodiments, teleconferencemanagement program 101 logs how recent each topic or concept isdiscussed, as well as the amount of time each topic or concept has beendiscussed. In some embodiments, conversation database 104 includesidentity information relating to conference participants.

FIG. 2 is a flow chart diagram depicting operational steps for ateleconference management program in accordance with at least oneembodiment of the invention. It should be appreciated that embodimentsof the present invention provide for the real-time analysis of meetingtopics to determine current, as well as future trends and themes thatmay be contextually relevant during the conference or meeting.Embodiments of the present invention further provide for analyzingconversational topics and themes over time to determine whether specificverbal communications and conversations are outside an expected contextof a current discussion.

In accordance with FIG. 2, the following exemplary scenario will beused. In this exemplary scenario, a teleconference is currently beingconducted to discuss planning for an automotive tradeshow. Currently,four conference lines (Line A, Line B, Line C, and Line D)(independently shown in FIG. 1) have joined the teleconference. Line Ais a mobile phone with a single participant currently sitting in awaiting area of an airport. Line B is a cordless phone with a singleparticipant sitting in an office. Line C is a speaker phone with a groupof participants located in a conference room. Line D is a mobile tabletwith a single participant located at home.

At step S200, teleconference management program 101 receives a pluralityof audio signals from plurality of user devices 103. In someembodiments, plurality of user devices 103 are connected to atelecommunications system via network 105. In some embodiments,teleconference management program 101 buffers or delays the audiosignals for an initial period of time (e.g., 5 seconds) to allowteleconference management program 101 to analyze the audio signalsbefore the audio reaches any conference members. Buffering or delayingaudio signals allows teleconference management program 101 to redact orfilter non-relevant conversations or background noises that deviate froma current topic of discussion prior to being heard by members of theteleconference. In alternative embodiments, teleconference managementprogram 101 does not buffer or delay the plurality of audio signals.Here, teleconference management program 101 analyzes the audio signalsin real-time.

At step S201, teleconference management program 101 identifies aplurality of utterances from the plurality of audio signals. Anutterance may generally be understood as a verbal communication (e.g.,word or statement), non-lexical communication (e.g., exclamations,sighs, laughs, cries, and shouts), or background noises detected byteleconference management program 101 during a teleconference. In someembodiments, teleconference management program 101 identifies utterancesbased on converting audio signals into text. In these embodiments,teleconference management program 101 converts audio signals into textusing speech-to-text (STT) software. In an embodiment, the text isconverted into a Unicode format (i.e., a universal encoding standardused for representing text for computer processing). In an embodiment,the text is converted into a speech synthesis mark-up language (SSML)format. In an embodiment, the raw text containing symbols (e.g., numbersand abbreviations) is converted into the equivalent of written-out wordsthrough text normalization (i.e., pre-processing or tokenization).

In some embodiments, teleconference management program 101 identifiesutterances without the use of STT software or natural languageprocessing (NLP) software. In these embodiments, teleconferencemanagement program 101 uses automatic speech recognition (ASR) softwareto identify utterances. ASR software breaks down each utterance intophonemes. Each phoneme is then analyzed in sequence. In an embodiment,teleconference management program 101 generates an acoustic model thattextually represents the relationship between each audio signal and thephonemes or other linguistic units that make up speech. The acousticmodel includes statistical representations of the sounds that make upeach word.

In some embodiments, teleconference management program 101 identifiesutterances based on comparing sounds corresponding to each audio signalwith word sequences. More specifically, teleconference managementprogram 101 compares sounds corresponding to each utterance to alanguage model. A language model provides context to distinguish betweenwords and phrases that sound similar (e.g., “recognize speech” and“wreck a nice beach” are pronounced similarly but have very differentmeanings). In an embodiment, teleconference management program 101compares sounds corresponding to each utterance to a positional languagemodel. A positional language model describes the probability of givenwords occurring close to one another, but not necessarily immediatelyadjacent, in a text.

In an embodiment, teleconference management program 101 segments eachaudio signal into one or more of the following speech units: phones,diphones, half-phones, syllables, morphemes, words, phrases, andsentences. In an embodiment, teleconference management program 101determines intonational attributes associated with the utterances.Intonational attributes may include, but are not limited to, pitchenvelope (i.e., a combination of the speaking fundamental frequency,pitch range, and the shape and timing of the pitch contour), overallspeech rate, utterance timing (i.e., duration of segments and pauses),vocal quality, and intensity (i.e., loudness). Teleconference managementprogram 101 stores the speech units and intonational attributescorresponding to the utterances in conversation database 104.

At step S202, teleconference management program 101 divides theplurality utterances into sets of utterances. In embodiments of theinvention, each set of utterances is based on a speaker's vocalidentity. Here, teleconference management program 101 uses speakerdiarisation software to identify when the same individual is speaking.Diarisation is the process of segmenting an audio signal into homogenoussegments according to the speaker identity. Speaker diarisation includesspeaker segmentation (i.e., finding speaker change points in an audiostream) and speaker clustering (i.e., grouping together speech segmentsbased on intonational attributes). In alternative embodiments, each setof utterances is divided based on a telecommunications line from whichan audio signal carrying the set of utterances is transmitted.

At step S203, teleconference management program 101 identifies anidentity associated with each set of utterances. In an embodiment,teleconference management program 101 uses speaker verification softwareto verify an identity of a speaker associated with a set of utterances.Here, a speech sample (i.e., utterance) is compared against a previouslycreated voice signature (i.e., voice print, template, or model). In anembodiment, teleconference management program 101 uses voice recognitionsoftware (i.e., speaker identification software) to identify an identityof a speaker associated with a set of utterances. Speaker identificationsoftware identifies a speaker based on unique characteristics includedwithin a speech sample. The speech sample is compared against multiplevoice prints in order to determine the best match. For example,teleconference management program 101 retrieves labeled training data(i.e., known vocal samples) of intonational attributes associated withpreviously recorded audio of meeting participants. Based on matching theintonational attributes of a known vocal sample with the intonationalattributes associated with a portion of the utterances received duringthe teleconference, a speaker's identity can be identified. In anembodiment, teleconference management program 101 uses a Gaussianmixture speaker model to identify an identity of a speaker associatedwith a set of utterances.

In some embodiments, teleconference management program 101 identifies anidentity of a speaker associated with a set of utterances via facialrecognition software. For example, teleconference management program 101captures an image of a speaker via a camera built into plurality of userdevices 103. In another example, teleconference management programbreaks down video received from a recording device built into pluralityof user devices 103 into multiple video frames. In these embodiments,teleconference management program 101 employs a speaker image datasetand image analysis software (i.e., comparing selected facial featuresfrom the image or video frame with facial features corresponding to thespeaker image dataset) to identify a speaker.

At step S204, teleconference management program 101 determines a contextassociated with each set of utterances. In some embodiments,teleconference management program 101 determines a context through theuse of text mining software to extract keywords from a textualtranscript corresponding to a set of utterances. Text mining (i.e., textdata mining, text analytics) is the process of deriving high-qualityinformation from text. Within the field of text mining, keywordextraction is the automatic identification of terms that best describeor characterize the subject of text document. Here, each set ofutterances is transcribed into text through STT software and keywordsare identified within the transcribed text document. In someembodiments, teleconference management program 101 determines a contextthrough the use of speech analytics software (i.e., audio miningsoftware) to spot keywords and phrases from a set of utterances. Here,phoneme sequences corresponding to the set of utterances are matchedwith phoneme sequences of words. It should be appreciated that by usingintermediate representations (including, but not limited to, phoneticposteriorgrams and lattice representations) to match phoneme sequences,a context may be determined without requiring the use of STT software.

At step S205, teleconference management program determines a context ofa conversation (i.e., a current topic of discussion) corresponding tothe plurality of utterances. In some embodiments, a current topic ofdiscussion is determined based, at least in part, through the use ofspeech analytics software. Speech analytics software is the process ofanalyzing categorical topics of discussion by isolating words andphrases that are most frequently used within a given time period andindicating whether the usage is trending up or down. For example, if theterm “catering” is identified from the plurality of utterances more thanfive times within a one minute time period, teleconference managementprogram 101 may determine that the current topic of discussion revolvesaround catering.

In some embodiments, a current topic of discussion is further determinedbased on matching contextual information presented during a topic ofdiscussion with the keywords or phrases identified from the plurality ofutterances. In an embodiment, teleconference management program 101 usesnamed entity recognition (NER) software to identify names of people,places, locations, organizations, etc. included in text, images, andvideo data presented during the teleconference. For example, names ofcatering companies are identified from a PDF document and, in response,are determined to match the current topic of discussion “catering.” Inan embodiment, teleconference management program 101 uses opticalcharacter recognition (OCR) software to convert images of typed,handwritten, or printed text into machine readable text. For example,names of a catering companies are identified from an image presented viaa video conferencing application and, in response, are determined tomatch the current topic of discussion “catering.” In an embodiment,teleconference management program 101 uses computer vision software(including object recognition software) to find and identify objects inan image or video sequence. Computer vision includes methods foracquiring, processing, analyzing, and understanding digital images. Forexample, a logo of a catering company is identified from video streamedvia a webinar application and, in response, are determined to match thecurrent topic of discussion “catering.”

At step S206, teleconference management program 101 analyzes therelevance of each set of utterances. In embodiments of the invention,teleconference management program 101 analyzes a relevance of each setof utterances based, at least in part, on comparing the contextassociated with each set of utterances with the current topic ofdiscussion. For example, as the teleconference progresses,teleconference management program 101 continues to track key topics ofdiscussion, as well as contexts associated with each set of utterances.The current topic of discussion revolves around venues. Currently, June,on Line D, is speaking about locations for the tradeshow. While June isspeaking, teleconference management program 101 detects that John, onLine A, is also speaking. Based on keywords and/or phrases associatedwith utterances from John, John's utterances are determined to beassociated with the context “music.” Since the context “music” is notcontextually relevant to the current topic of discussion “venues,”teleconference management program 101 will determine that John's set ofutterances are not relevant to the current discussion.

It should be noted that what is deemed to be contextually relevant maychange as a discussion transitions from one topic to another.Accordingly, in some embodiments, a relevance of each set of utterancesis further based on inferring additional topics that may be contextuallyrelevant to the current topic of discussion. In these embodiments,teleconference management program 101 uses concept expansion software(i.e., semantic lexicon induction software or semantic set expansionsoftware) to infer additional topics that may potentially be related tothe current topic of discussion. Concept expansion software provides forthe development and expansion of semantic classes.

For example, at the beginning of the teleconference, the current topicof discussion is determined to generally revolve around planning for theautomotive tradeshow. Based on mentioning the term “tradeshow” multipletimes within a given time period (e.g., 20 seconds), the concept of thesemantic class “tradeshow” is expanded to include concepts and termsassociated with a tradeshow, such as venue, catering, invitation,seating, companies, and automotive products. Each of these concepts maythen be further expanded. For example, the semantic class “automotiveproducts” may be expanded to include tires, brakes, engines, andtransmissions. Thus, although a discussion may revolve around aparticular topic, teleconference management program 101 may determinethat a context associated with a set of utterances that appears todeviate from a current topic of discussion is in fact relevant to thecurrent discussion.

In some embodiments, analyzing the relevance of each set of utterancesis further based on identifying dialog acts. A dialog act is aspecialized speech act, such as greetings, meta questions (e.g., “Whatcan I say?”), yes or no questions, statements, and requests. Forexample, a current discussion revolves around determining a venue forthe automotive tradeshow. Jim, a speaker on Line B, is currentlycontrolling the conversation since he is located in the city hosting thetradeshow. At times, John, on Line A, attempts to interject into thediscussion. Although John's words are determined to be in conflict withthe current conversation headed by Jim, teleconference managementprogram 101 determines that John's interjection is merely a statement orrequest, such as “excuse me” or “may I speak” and thus are relevant tothe current conversation.

At step S207, teleconference management program 101 dynamically mutes anaudio signal corresponding to a non-relevant set of utterances. Inembodiments of the invention, an audio signal is muted based, at leastin part, on a determination that at least a portion of a set ofutterances is non-relevant to a current topic of discussion. In someembodiments, a decision to dynamically mute an audio signal is furtherbased on a weighted score assigned to each speaker. In this embodiment,teleconference management program 101 assigns a weighted score to eachspeaker based on the speaker's identity (e.g., job title (e.g.,president, CEO, manager, supervisor, and employee) or occupation (e.g.,political figure, professor, and scientist). For example, Jill, on LineC, is identified as an employee of the company hosting the tradeshow.Jill is currently discussing potential catering companies for thetradeshow. However, the president of the company, June, on Line D hasinterjected with a question about potential venues for the tradeshow.Although the topic of “venues” may be non-relevant to the currentdiscussion of “catering,” if June's weighted score is greater thanJill's weighted score, teleconference management program 101 will notmute Line D. Similarly, a higher score may be given to the person who isleading the conversation, since it is less likely that this personshould be muted due to their importance to a conversation.

In some embodiments, a decision to dynamically mute an audio signal isfurther based on a likelihood of a speaker to engage in secondaryconversations or generate background noises. A secondary conversationmay generally be understood as a set of utterances that is not relevantto a current topic of discussion. In these embodiments, an audio signalassociated with a speaker is flagged if the speaker has partaken insecondary conversations or generated background noises above a giventhreshold (e.g., more than three secondary conversations over a periodof one month). In an embodiment, teleconference management program 101dynamically mutes an audio line of a speaker who has been flagged fasterthan other speakers who have not been flagged. Here, the term “faster”pertains to an amount of time for a determination to be reached that aconversation is not relevant to a current topic of discussion. Forexample, teleconference management program 101 determines thatconversations by both John and Jim are likely to be non-relevant to thecurrent discussion about venues. However, if John's line has beenflagged, teleconference management program 101 may determine in ashorter amount of time that John's conversation is likely to benon-relevant. Accordingly, John's line is muted sooner than Jim's line.

In alternative embodiments, teleconference management program 101dynamically lowers the volume of an audio signal. In an embodiment,teleconference management program 101 dynamically lowers the volume ofan audio signal based on a location from which the audio signal istransmitted. Here, teleconference management program 101 determines alikelihood of incurring secondary conversations and background noisesbased on location. For example, John, on Line A, is located in anairport, while Jim, on Line B, is located in an office setting. Sincesecondary conversations and background noises are more likely to occurin an airport than in an office setting, teleconference managementprogram 101 lowers the volume of a microphone of built into John'smobile phone. However, John may manually increase the microphone volumeif he needs to speak. Once the speaker is finished speaking,teleconference management program 101 once again automatically lowersthe microphone volume. In an embodiment teleconference managementprogram 101 dynamically lowers an audio signal based on an identity of aspeaker associated with the audio signal. Here, teleconferencemanagement program 101 determines a likelihood of incurring secondaryconversations and background noises based on speaker identity. Forexample, if a speaker has been flagged (i.e., the speaker has partakenin secondary conversations or generated background noises above a giventhreshold), the speaker's microphone is dynamically lowered.

FIG. 3 is a block diagram depicting components of a computer 300suitable for executing teleconference management program 101, inaccordance with at least one embodiment of the invention. FIG. 3displays the computer 300, one or more processor(s) 304 (including oneor more computer processors), a communications fabric 302, a memory 306including, a RAM 316, and a cache 318, a persistent storage 308, acommunications unit 312, I/O interfaces 314, a display 322, and externaldevices 320. It should be appreciated that FIG. 3 provides only anillustration of one embodiment and does not imply any limitations withregard to the environments in which different embodiments may beimplemented. Many modifications to the depicted environment may be made.

As depicted, the computer 300 operates over the communications fabric302, which provides communications between the computer processor(s)304, memory 306, persistent storage 308, communications unit 312, andinput/output (I/O) interface(s) 314. The communications fabric 302 maybe implemented with any architecture suitable for passing data orcontrol information between the processors 304 (e.g., microprocessors,communications processors, and network processors), the memory 306, theexternal devices 320, and any other hardware components within a system.For example, the communications fabric 302 may be implemented with oneor more buses.

The memory 306 and persistent storage 308 are computer readable storagemedia. In the depicted embodiment, the memory 306 comprises a randomaccess memory (RAM) 316 and a cache 318. In general, the memory 306 maycomprise any suitable volatile or non-volatile one or more computerreadable storage media.

Program instructions for teleconference management program 101 may bestored in the persistent storage 308, or more generally, any computerreadable storage media, for execution by one or more of the respectivecomputer processors 304 via one or more memories of the memory 306. Thepersistent storage 308 may be a magnetic hard disk drive, a solid statedisk drive, a semiconductor storage device, read-only memory (ROM),electronically erasable programmable read-only memory (EEPROM), flashmemory, or any other computer readable storage media that is capable ofstoring program instructions or digital information.

The media used by the persistent storage 308 may also be removable. Forexample, a removable hard drive may be used for persistent storage 308.Other examples include optical and magnetic disks, thumb drives, andsmart cards that are inserted into a drive for transfer onto anothercomputer readable storage medium that is also part of the persistentstorage 308.

The communications unit 312, in these examples, provides forcommunications with other data processing systems or devices. In theseexamples, the communications unit 312 may comprise one or more networkinterface cards. The communications unit 312 may provide communicationsthrough the use of either or both physical and wireless communicationslinks. In the context of some embodiments of the present invention, thesource of the various input data may be physically remote to thecomputer 300 such that the input data may be received and the outputsimilarly transmitted via the communications unit 312.

The I/O interface(s) 314 allow for input and output of data with otherdevices that may operate in conjunction with the computer 300. Forexample, the I/O interface 314 may provide a connection to the externaldevices 320, which may be as a keyboard, keypad, a touch screen, orother suitable input devices. External devices 320 may also includeportable computer readable storage media, for example thumb drives,portable optical or magnetic disks, and memory cards. Software and dataused to practice embodiments of the present invention may be stored onsuch portable computer readable storage media and may be loaded onto thepersistent storage 308 via the I/O interface(s) 314. The I/Ointerface(s) 314 may similarly connect to a display 322. The display 322provides a mechanism to display data to a user and may be, for example,a computer monitor.

The present invention may be a system, a method, and/or a computerprogram product at any possible technical detail level of integration.The computer program product may include a computer readable storagemedium (or media) having computer readable program instructions thereonfor causing a processor to carry out aspects of the present invention.

The computer readable storage medium can be a tangible device that canretain and store instructions for use by an instruction executiondevice. The computer readable storage medium may be, for example, but isnot limited to, an electronic storage device, a magnetic storage device,an optical storage device, an electromagnetic storage device, asemiconductor storage device, or any suitable combination of theforegoing. A non-exhaustive list of more specific examples of thecomputer readable storage medium includes the following: a portablecomputer diskette, a hard disk, a random access memory (RAM), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a static random access memory (SRAM), a portablecompact disc read-only memory (CD-ROM), a digital versatile disk (DVD),a memory stick, a floppy disk, a mechanically encoded device such aspunch-cards or raised structures in a groove having instructionsrecorded thereon, and any suitable combination of the foregoing. Acomputer readable storage medium, as used herein, is not to be construedas being transitory signals per se, such as radio waves or other freelypropagating electromagnetic waves, electromagnetic waves propagatingthrough a waveguide or other transmission media (e.g., light pulsespassing through a fiber-optic cable), or electrical signals transmittedthrough a wire.

Computer readable program instructions described herein can bedownloaded to respective computing/processing devices from a computerreadable storage medium or to an external computer or external storagedevice via a network, for example, the Internet, a local area network, awide area network and/or a wireless network. The network may comprisecopper transmission cables, optical transmission fibers, wirelesstransmission, routers, firewalls, switches, gateway computers and/oredge servers. A network adapter card or network interface in eachcomputing/processing device receives computer readable programinstructions from the network and forwards the computer readable programinstructions for storage in a computer readable storage medium withinthe respective computing/processing device.

Computer readable program instructions for carrying out operations ofthe present invention may be assembler instructions,instruction-set-architecture (ISA) instructions, machine instructions,machine dependent instructions, microcode, firmware instructions,state-setting data, or either source code or object code written in anycombination of one or more programming languages, including an objectoriented programming language such as Smalltalk, C++ or the like, andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The computerreadable program instructions may execute entirely on the user'scomputer, partly on the user's computer, as a stand-alone softwarepackage, partly on the user's computer and partly on a remote computeror entirely on the remote computer or server. In the latter scenario,the remote computer may be connected to the user's computer through anytype of network, including a local area network (LAN) or a wide areanetwork (WAN), or the connection may be made to an external computer(for example, through the Internet using an Internet Service Provider).In some embodiments, electronic circuitry including, for example,programmable logic circuitry, field-programmable gate arrays (FPGA), orprogrammable logic arrays (PLA) may execute the computer readableprogram instructions by utilizing state information of the computerreadable program instructions to personalize the electronic circuitry,in order to perform aspects of the present invention.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems), and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer readable program instructions.

These computer readable program instructions may be provided to aprocessor of a general purpose computer, special purpose computer, orother programmable data processing apparatus to produce a machine, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, create means forimplementing the functions/acts specified in the flowchart and/or blockdiagram block or blocks. These computer readable program instructionsmay also be stored in a readable storage medium that can direct acomputer, a programmable data processing apparatus, and/or other devicesto function in a particular manner, such that the computer readablestorage medium having instructions stored therein comprises an articleof manufacture including instructions which implement aspects of thefunction/act specified in the flowchart and/or block diagram block orblocks.

The computer readable program instructions may also be loaded onto acomputer, other programmable data processing apparatus, or other deviceto cause a series of operational steps to be performed on the computer,other programmable apparatus or other device to produce a computerimplemented process, such that the instructions which execute on thecomputer, other programmable apparatus, or other device implement thefunctions/acts specified in the flowchart and/or block diagram block orblocks.

The flowchart and block diagrams in the Figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments of the present invention. In this regard, each block in theflowchart or block diagrams may represent a module, segment, or portionof computer program instructions, which comprises one or more executableinstructions for implementing the specified logical function(s). In somealternative implementations, the functions noted in the block may occurout of the order noted in the Figures. For example, two blocks shown insuccession may, in fact, be executed substantially concurrently, or theblocks may sometimes be executed in the reverse order, depending uponthe functionality involved. It will also be noted that each block of theblock diagrams and/or flowchart illustration, and combinations of blocksin the block diagrams and/or flowchart illustration, can be implementedby special purpose hardware-based systems that perform the specifiedfunctions or acts or carry out combinations of special purpose hardwareand computer instructions.

The descriptions of the various embodiments of the present inventionhave been presented for purposes of illustration, but are not intendedto be exhaustive or limited to, the embodiments disclosed. Manymodifications and variations will be apparent to those of ordinary skillin the art without departing from the scope and spirit of the describedembodiments. The terminology used herein was chosen to best explain theprinciples of the embodiments, the practical application or technicalimprovement over technologies found in the marketplace, or to enableothers of ordinary skill in the art to understand the embodimentsdisclosed herein.

What is claimed is:
 1. A computer-implemented method comprising:identifying a first set of utterances from a plurality of utterances,wherein: the plurality of utterances is associated with a conversation;and the plurality of utterances is transmitted via a plurality of audiosignals; mining the first set of utterances for a first context;determining that the first context associated with the first set ofutterances is not relevant to a second context associated with theconversation; and muting, on a dynamic basis, for at least a firstperiod of time, a first audio signal in the plurality of audio signalscorresponding to the first set of utterances.
 2. Thecomputer-implemented method of claim 1, further comprising: buffering,for an initial period of time, the plurality of utterances transmittedvia the plurality of audio signals; and redacting the first set ofutterances prior to being transmitted via the first audio signalcorresponding to the first set of utterances.
 3. Thecomputer-implemented method of claim 1, further comprising: monitoringthe first audio signal corresponding to the first set of utterances;determining that a second set of utterances corresponding to the firstaudio signal is relevant to the conversation; and unmuting, on a dynamicbasis, for at least a second period of time, the first audio signal. 4.The computer-implemented method of claim 1, further comprising:generating a transcript of the first set of utterances corresponding tothe first audio signal that is muted; and presenting the transcript inconjunction with the conversation.
 5. The computer-implemented method ofclaim 1, further comprising: transmitting a notification that the firstaudio signal is muted.
 6. The computer-implemented method of claim 1,further comprising: identifying a location from which the first audiosignal in the plurality of audio signals is transmitted; determining,based on the location, a likelihood that the first audio signal willinclude a set of utterances that are not relevant to the conversation;and lowering, on a dynamic basis, a volume of the first audio signal. 7.The computer-implemented method of claim 1 further comprising:identifying an identity of a speaker associated with the first audiosignal; determining, based on the identity of the speaker, a likelihoodthat the first audio signal will include a set of that are not relevantto the conversation; and lowering, on a dynamic basis, the volume of theaudio signal.
 8. A computer program product, the computer programproduct comprising one or more computer readable storage media andprogram instructions stored on the one or more computer readable storagemedia, the program instructions comprising instructions to: identify afirst set of utterances from a plurality of utterances, wherein: theplurality of utterances is associated with a conversation; and theplurality of utterances is transmitted via a plurality of audio signals;mine the first set of utterances for a first context; determine that thefirst context associated with the first set of utterances is notrelevant to a second context associated with the conversation; and mute,on a dynamic basis, for at least a first period of time, a first audiosignal in the plurality of audio signals corresponding to the first setof utterances.
 9. The computer program product of claim 8, furthercomprising instructions to: buffer, for an initial period of time, theplurality of utterances transmitted via the plurality of audio signals;and redacting the first set of utterances prior to being transmitted viathe first audio signal corresponding to the first set of utterances. 10.The computer program product of claim 8, further comprising instructionsto: monitor the first audio signal corresponding to the first set ofutterances; determine that a second set of utterances corresponding tothe first audio signal is relevant to the conversation; and unmute, on adynamic basis, for at least a second period of time, the first audiosignal.
 11. The computer program product of claim 8, further comprisinginstructions to: generate a transcript of the first set of utterancescorresponding to the first audio signal that is muted; and present thetranscript in conjunction with the conversation.
 12. The computerprogram product of claim 8, further comprising instructions to: transmita notification that the first audio signal is muted.
 13. The computerprogram product of claim 8, further comprising instructions to: identifya location from which the first audio signal in the plurality of audiosignals is transmitted; determine, based on the location, a likelihoodthat the first audio signal will include a set of utterances that arenot relevant to the conversation; and lower, on a dynamic basis, avolume of the first audio signal.
 14. The computer program product ofclaim 8, further comprising instructions to: identify an identity of aspeaker associated with the first audio signal; determine, based on theidentity of the speaker, a likelihood that the first audio signal willinclude a set of that are not relevant to the conversation; and lower,on a dynamic basis, the volume of the audio signal.
 15. A computersystem, the computer system comprising: one or more computer processors;one or more computer readable storage media; computer programinstructions; the computer program instructions being stored on the oneor more computer readable storage media for execution by the one or morecomputer processors; and the computer program instructions comprisinginstructions to: identify a first set of utterances from a plurality ofutterances, wherein: the plurality of utterances is associated with aconversation; and the plurality of utterances is transmitted via aplurality of audio signals; mine the first set of utterances for a firstcontext; determine that the first context associated with the first setof utterances is not relevant to a second context associated with theconversation; and mute, on a dynamic basis, for at least a first periodof time, a first audio signal in the plurality of audio signalscorresponding to the first set of utterances.
 16. The computer system ofclaim 15, further comprising instructions to: buffer, for an initialperiod of time, the plurality of utterances transmitted via theplurality of audio signals; and redacting the first set of utterancesprior to being transmitted via the first audio signal corresponding tothe first set of utterances.
 17. The computer system of claim 15,further comprising instructions to: monitor the first audio signalcorresponding to the first set of utterances; determine that a secondset of utterances corresponding to the first audio signal is relevant tothe conversation; and unmute, on a dynamic basis, for at least a secondperiod of time, the first audio signal.
 18. The computer system of claim15, further comprising instructions to: generate a transcript of thefirst set of utterances corresponding to the first audio signal that ismuted; and present the transcript in conjunction with the conversation.19. The computer system of claim 15, further comprising instructions to:transmit a notification that the first audio signal is muted.
 20. Thecomputer system of claim 15, further comprising instructions to:identify a location from which the first audio signal in the pluralityof audio signals is transmitted; determine, based on the location, alikelihood that the first audio signal will include a set of utterancesthat are not relevant to the conversation; and lower, on a dynamicbasis, a volume of the first audio signal.